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Cell Biochemistry Martinsried |
G.Valet, BEM van Driel1), C.J.F. van Noorden1)
1. Concept:
Malignant tumor cells may show metabolic differences as compared
to the normal surrounding tissue. Such differences in combination with
other clinical information could be useful for individualized post-surgery
disease course prediction by
cytomics (multiparametric evaluation of
molecular markers in heterogeneous tissues or cell suspensions).
2. Realisation:
The glucose-6-phosphate dehydrogenase (G6PDH)
oxygen insensitivity assay, CuZn- and Mn-superoxide dismutase
(SOD) and lipid peroxidation levels were determined
by absorption cytophotometry in frozen sections of
colorectal carcinomas and adjacent normal mucosa tissue. The
measured values as well as the calculated ratios
and differences between cancer and normal tissue in each patient,
furthermore the patient age, Dukes' tumor stage, lymph node
metastasis and blood vessel invasion status that is
altogether 29 parameters were analysed by
CLASSIF1
data pattern analysis.
3. Results:
A data pattern of 11 parameters permitted to predict non-surviving
and surviving patients with predictive values of 100% and 59.5%
in the learning set and of 100% and 62.5% in the
test set of unknown patients, showing robust
classification with the selected parameter patterns
for prospective classification of unknown patients.
4. Conclusion:
Data pattern classification of this still limited number of
patients shows that the determination of molecular markers
in tissue sections by absorption cytophotomtry has
a potential for individualized disease course prediction.
It exceeds in any case the capacities of histopathological
grading and staging system by morphological parameters alone.
5. Literature References:
1.
BEM van Driel, GK Valet, H Lyon, U Hansen, JY Song,
CJF van Noorden: (1999)
Prognostic estimation of survival of colorectal cancer patients with
quantitative histochemical assay of G6PDH activity and the
multiparameter classification program CLASSIF1.
Cytometry(Comm.Clin.Cytom.) 38:176-183
© 2024 G.Valet |